1. Field of the Invention
The present invention relates to a method for structural health monitoring (SHM) using a sensor system and ultrasound. The sensor system may be used to monitor the structural health of structures including civil engineering structures, such as bridges, buildings and underwater structures, critical structural elements in the automobile, aerospace and petrochemical industry as well as storage structures and reactors.
2. Description of the Related Technology
SHM is used to maintain and preserve the structural integrity of structures, which degrade over time from exposure to excipient factors, such as earthquakes, storms, pollution, vibration, traffic, and other environmental factors. In the last few decades there has been tremendous interest in developing methods and sensors, such as strain gages, displacement sensors, accelerometers, magneto-strictive sensors, fiber optic sensors and piezoelectric sensors, for detecting structural degradation or damage.
Current SHM techniques utilize either global sensing methods or local sensing methods. Global dynamic methods excite a structure using low frequency acoustic waves and detect the resulting corresponding natural frequencies of the structure. The natural frequency data may then be manipulated with various algorithms to locate and quantify damage in simple structures. Global dynamic methods, however, rely on a relatively small number of low order modes that are insufficiently sensitive to detect localized incipient damage, which may be critical to structural integrity. Additionally, the application and detection of low frequency excitation, typically below 100 Hz, is easily contaminated by surrounding vibrations and noise. Global static methods, such as static displacement response and static strain measurement, are also impractical since they are too expensive to enable a cost and time efficient structural evaluation.
Local sensing methods, such as ultrasonic wave propagation techniques, acoustic emissions, magnetic field analysis, electrical methods, dye penetrant testing, impact echo testing and X-ray radiography, are also problematic. A common limitation of local sensing methods is that a probe needs to be moved around the structure to first identify a potential site of structural damage if the location of structural weakness is not already known. Attempts to overcome this difficulty, with varying success, included measuring the response from an array of piezoelectric patches on the surface, magneto-elastic sensors and fiber Bragg grating methods.
Of the various local sensing methods, ultrasonic wave propagation is one of the most promising, enabling detection of damage and structural flaws with a high degree of sensitivity. Examples of ultrasonic wave propagation are disclosed in U.S. Pat. No. 6,996,480 and Lars Lading, et al., “Fundamentals for Remote Structural Health Monitoring of Wind Turbine Blades”, Riso National Laboratory, 2002. The main drawback of the ultrasonic method is that it requires several transducers to be installed at various locations to monitor a particular structure due to the attenuation and absorption of sound waves in these structures. Often, ultrasonic transducer installation is time-consuming and expensive making such methods impractical.
Ultrasonic methods also typically require complex data processing. In addition to being expensive, ultrasonic methods also render the structure unavailable for use throughout the duration of the test. Due to the nature of sound waves, excitation means for the ultrasonic transducers has to be coupled directly onto the structure being monitored. In addition, such systems typically only work over relatively narrow temperature ranges and under limited environmental conditions.
In spite of recent innovations, as far as the inventors are aware, no sensor, to date, enables highly sensitive detection of various types of deformation under a wide range of variable atmospheric, corrosive and temperature conditions. Current sensors additionally require complex data processing and large amounts of information to analyze structural deformation. Therefore, there is a need to develop a sensor system capable of extracting important parameters from minimal amounts of data using simple data processing techniques and which is further capable of highly sensitive detection irrespective of environmental conditions.